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Image restoration using regularized inverse filtering and adaptive threshold wavelet denoising
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Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet denoising stage . The choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet sub band coefficients like standard deviation, arithmetic mean and geometrical mean . The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by this method .

Experimental results on test image by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR). Here, to prove the efficiency of this method in image restoration , we have compared this with various restoration  methods like Wiener filter alone and inverse filter.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
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The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges
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The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
Application of WDR Technique with different Wavelet Codecs for Image Compression
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FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

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Scopus (10)
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
Steganography in Audio Using Wavelet and DES
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In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secr

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Scopus (24)
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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Prediction Using Artificial Neural Network of Bed Porosity and Solid Holdup in Viscous 3-Phase Inverse Fluidization
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In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using simulation to compare between parametric and nonparametric transfer function model
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In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

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Publication Date
Sun Oct 01 2023
Journal Name
Int. J. Nonlinear Anal. Appl
Adaptive 1-D polynomial coding to compress color image with C421
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